A Data-Integrated Simulation Approach for the Cooling Effect of Leaves During Urban Heat Waves

Current global climate developments suggest that extreme weather conditions will occur more often and more intense than in the past. One example of such severe conditions are heat waves, which will strongly influence life in big cities. Buildings and pavements store heat during the day and release it during the night, leading to constantly high temperatures without periods of cooling in between. Plants can help to reduce the impact of heat waves in big cities due to evaporative cooling. Leaf structures, stomata patterns and evaporation rates are important factors for climate regulation. Micro-scale processes such as water transport within the leaf, drop formation on the leaf surface and evaporation into the surrounding determine the cooling effect. In addition, environmental temperature changes and wind conditions have a significant impact. Our project focuses on the description of evapotranspiration processes, i. e. the transport of water, gas and energy in the direct environment of a plant leaf. In a first step, the leaf is described in a static manner. In the second step, leaf motion in the wind field as well as the influence of radiation are taken into account.

Cooperations with the University of Ulm and the ETH Zürich will allow to describe the leaf structures in detail, which is a prerequisite to model leaves as a porous medium. The detailed knowledge of the leaf structure is then applied to a pore-network model (PNM) to resolve the stomata discretely. With the PNM, thermodynamic influences of the leaf structure can be deduced under the consideration of drops. The highly-resolved simulation results together with measured data from partners yield a data-rich system. This system can then be used as a learning basis to improve the parameterization of an REV-scale model with the help of machine learning.